Exercise 1_2_3: Statistical Software Files

Now we are in the second exercise session. Non-flat files were promised, so please load the GESIS Panel COVID-19 survey data.

This first part of the exercises only deals with importing data. Later, in the second part, we will turn to labelling and exporting.

1

Load the GESIS Panel COVID-19 survey data.

Clues

You can either load the SPSS or Stata file. In both cases, you need the haven package.

solution

library(haven)

gp_covid <-
  read_spss("./data/ZA5667_v1-1-0.sav")

In contrast to the flat files, such as CSV, the variables now have labels.

2

Print the labels of the first ten variables in the dataset.

Clues

You can print labels with the function sjlabelled::get_label(your_data), but you have to make sure only to print the first ten variables.

solution

library(sjlabelled)

get_label(gp_covid[1:10])

##                                za_number                                  version                                      doi 
##              "Studiennummer des Archivs" "Versionskennung und -datum des Archivs"        "Digital Object Identifier (doi)" 
##                                       id                                   cohort                                      sex 
##                           "Befragten-ID"                   "Rekrutierungskohorte"                             "Geschlecht" 
##                                  age_cat                            education_cat                        intention_to_vote 
##                   "Alter, kategorisiert"                 "Bildung, kategorisiert"               "Sonntagsfrage (gbzc011a)" 
##                          choice_of_party 
##         "Sonntagsfrage Wahlentscheidung"

Unfortunately, it’s all in German. Imagine you are an education researcher, and you are interested in the variable education_cat. So you may want to consider translating the variable into English.

3

Change the variable label of education_cat from “Bildung, kategorisiert” to “Education, categorized”.

Clues

There a two ways: You can either use the function sjlabelled::set_label() or do it in a pipe with sjlabelled::var_labels().

solution

# either
gp_covid$education_cat <- 
  set_label(
    gp_covid$education_cat, 
    label = "Education, categorized"
  )

# or
library(dplyr)

gp_covid <- 
  gp_covid %>% 
  var_labels(
    education_cat = "Education, categorized"
  )

# proof
get_label(gp_covid$education_cat)

## [1] "Education, categorized"

Your colleague asks you to provide your new data after changing labels and stuff. Unfortunately, she does not use R or SPSS and asks you to export your data as a Stata file.

4

Export your data as a Stata file.

Clues

As in the case of importing you, again, need the haven package.

solution

write_stata(gp_covid, "gesis_panel_corona_fancy_panels_final_final.dta")